Master Concurrent Queues with SKIP LOCKED: The Secret to High-Performance PostgreSQL Systems
Hi everyone 👋
Today I’m excited to share a deep-dive blog post I recently published on Medium, where I explore a powerful technique for improving performance in high-concurrency systems: PostgreSQL’s SKIP LOCKED.
👉 Read the full article here:
Master Concurrent Queues with SKIP LOCKED – Boost Your System’s Performance
🚨 Why this matters
Task queues are a foundational pattern in modern backend systems, especially microservice-based architectures. Whether you're managing job processors, background workers, or retry mechanisms, efficient concurrency is always a challenge.
The problem?
Using naïve locking mechanisms often leads to:
Deadlocks
Idle workers
Throughput bottlenecks
That’s where SKIP LOCKED comes in.
🧠 What you’ll learn from the blog:
✅ The real-world problem of multiple consumers polling from the same task queue.
✅ How PostgreSQL’s default row locking (SELECT ... FOR UPDATE) can cause contention.
✅ The magic of FOR UPDATE SKIP LOCKED — and how it avoids blocking by skipping locked rows.
✅ Step-by-step examples and SQL queries to implement this in your system.
✅ Benchmarks and performance observations from production-inspired scenarios.
⚙️ Practical Use Cases
If you're building or maintaining any of the following, this post is for you:
Background job systems (e.g., Sidekiq, Celery, Resque clones)
Microservice worker queues
Cron-based batch processing pipelines
Distributed task schedulers
Systems with retry/failure queues
🧪 Bonus: Performance Wins
This isn’t just theory. I show how using SKIP LOCKED allows multiple workers to safely and concurrently process jobs without stepping on each other, improving throughput and reducing lock wait times.
You’ll walk away with:
A better understanding of PostgreSQL internals
Real code you can adapt for production
A strategy to eliminate bottlenecks in your queue-based systems
🔗 Read It Now
📖 Master Concurrent Queues with SKIP LOCKED – Boost Your System’s Performance
💬 I'd love to hear your thoughts, feedback, or how you've handled concurrency in your systems. Feel free to reply or leave a comment.
Stay tuned—I’ll soon share more deep dives into scaling, observability, and system design based on my real-world backend engineering experiences.
Until next time 👋
– Shubham Gautam